Image information, be it color or black and white, is commonly generated in a bitmap format where the bitmap comprises a plurality of gray level pixels, i.e. pixels that are defined by digital values, each value representing a gray level among a number of gray levels. Thus, in a 8 bit system, 256 levels of gray or 256 colors are present, where each level represents an increment of gray between black and white. In the case of color bitmaps, where three defining colors or separations each include 256 levels of information, there may be more than 16 million colors defined by a gray bitmap.
Usually, bitmaps in such a gray level format are unprintable by standard printers. Standard printers print in a limited number of levels, either a spot or a no spot in the binary case, or a limited number of levels associated with the spot, for example, four in the quaternary case. Accordingly, it is necessary to reduce the gray level image data to a limited number of levels so that it is printed. Besides gray level information derived by scanning, certain processing techniques such as those described, for example, in U.S. patent application Ser. No. 07/600,542, entitled, "Method for Making Image Conversions With Error Diffusion" by R. Eschbach, produce gray level pixel values which require conversion to a limited set of "legal" or output values.
One standard method of converting gray level pixel values to binary level pixel values is through the use of dithering or halftoning processes. In such arrangements, over a given area having a number of gray pixels therein, each pixel value of an array of gray level pixels within the area is compared to one of a set of preselected thresholds (the thresholds are stored as a dither matrix and the repetitive pattern generated by this matrix is considered a halftone cell) as taught, for example, in U.S. Pat. No. 4,149,194 to Holladay. The effect of such an arrangement is that, for an area where the image is gray, some of the thresholds within the dither matrix will be exceeded, i.e. the image value at that specific location is larger than the value stored in the dither matrix for that same location, while others are not. In the binary case, the pixels or cell elements for which the thresholds are exceeded might be printed as black, while the remaining elements are allowed to remain white, dependent on the actual physical quantity described by the data. The effect of the distribution of black and white over the halftone cell is integrated by the human eye as gray. Dithering or halftoning presents problems, however, in that the amount of gray within an original image is not maintained exactly over an area, because the finite number of elements inside each dither matrix--and therefore halftone cell--only allows the reproduction of a finite number of gray levels, i.e. equal or less than the number of elements in the cell plus one, or less. The error arising from the difference between the output pixel value and the actual gray level pixel value at any particular cell is simply thrown away. This results in a loss of image information. In particular, dithering introduces coarse quantization artifacts which are visible in the image areas where the scene has little variation. This is also known as "banding", and is caused by the limited number of output gray levels available. The "banding" artifacts generally increase with decreasing cell size, which is identical to a decrease in the number of levels that can be represented by the halftone cell.
Algorithms that convert gray images to binary or other number on level images while attempting to preserve local density exist, and include among them error diffusion, as taught, for example, in "An Adaptive Algorithm for Spatial Greyscale" by Floyd and Stienberg, Proceedings of the SID 17/2, 75-77 (1976) (hereinafter, "Floyd and Steinberg"). Another, more elaborate method would be the error diffusion technique of U.S. Pat. No. 5,045,952 to Eschbach, which serves to provide image dependent edge enhancement, assigned to the same assignee as the present invention. Additional modifications to the error diffusion algorithm as taught by Floyd and Steinberg have been proposed, e.g.: a different weighting matrix, as taught, for example, in "A Survey of Techniques for the Display of Continuous Tone Pictures on Bilevel Displays" by Jarvis et al., Computer Graphics and Image Processing, Vol. 5., pp. 13-40 (1976), and in "MECCA--A Multiple-Error Correction Computation Algorithm for Bi-Level Image Hardcopy Reproduction" by Stucki, IBM Res. Rep. RZ1060 (1981). Modifications of the error calculation and weight allocation have been taught, for example, in U.S. Pat. No. 4,924,322 to Kurosawa et. al., U.S. Pat. No. 4,339,774 to Temple, and U.S. Pat. No. 4,955,065, to Ulichney. Other error diffusion methods include U.S. patent application Ser. No. 07/600,542, entitled "Method of Making Image Conversions with Error Diffusion" to Eschbach; Ser. No. 07/672,987, entitled "Method of Error Diffusion with Application of Multiple Error Diffusion Matrices" by Eschbach; Ser. No. 07/755,380, entitled "Method for Quantization of Gray Level Pixel Data with Application of Under Compensated Error Diffusion", by Eschbach et al., all assigned to the same assignee as the present invention.
Error diffusion attempts to maintain gray by making the conversion from gray pixels to binary or other level pixels on a pixel-by-pixel basis. The procedure examines each pixel with respect to a threshold or set of thresholds, and the difference between the gray level pixel value and the outout value is forwarded to a selected group or set of neighboring pixels, in accordance with a weighting scheme.
Another modification to the method error diffusion was taught by Billotet-Hoffmann and Bryngdahl, Proceedings of the SID, Vol. 24/3, (1983), pp. 253-258 (hereinafter, Billotet-Hoffmann and Bryngdahl). A dither matrix is used as a threshold for error diffusion, to alleviate the problems of undesired patterns generally produced by the error diffusion algorithm. Notably, however, in Billotet-Hoffmann and Bryngdahl, the maximum dynamic range of the proposed threshold modification is set to .alpha.=1 (page 257 in the aforementioned reference).
A problem noted with the use of the standard error diffusion algorithms for printing applications is the production of large numbers of isolated black and/or white pixels which are non-printable by many types of printers. The algorithm taught by Billotet-Hoffmann and Bryngdahl does not improve the printability of the general error diffusion algorithm. A method to overcome the printability problem is taught by U.S. Pat. No. 4,654,721 to Goertzel, where a method is shown to convert a continuous tone image to a bilevel pixel image. The total error generated in one halftone cell is distributed to a predetermined number of adjacent halftone cells. In this way, printable images are generated, while the banding artifact is reduced, by alternating between fixed output dot patterns. Because of an inherent lack of partial dots in this process, evidenced as a loss in sharpness, edge detection and sharpening was included. See, also, "Digital Halftoning in the IBM 4250 Printer" by Goertzel et al. (Goertzel), IBM J. Res. Develop., Vol 31, No. 1, January, 1987. U.S. patent application Ser. No. 07/583,337 by Shiau, and Ser. No. 07/775,201 to Fan, teach the use of similar methods to reduce a continuous tone image to a multilevel pixel image with diffusion of error between adjacent cells.